循环水系统节水措施思考

通过对循环水系统节水措施的思考,简单介绍在循环水节水措施中提高浓缩倍数是比较有效的方法,同时针对较高浓缩倍数下循环水运行时带来的不利因素,提出了一些可以采用的控制技术措施,以及一些在循环水节水中的现场管理措施.     

凝汽器在线能效评估方法在电厂中的应用

凝汽器在线能效评估方法可以实时计算凝汽器的清洁因子和背压损失,并用其评估凝汽器效率。使用凝汽器在线能效评估方法分析某电厂循环水化学品方案调整对凝汽器能效的影响,并指导药剂方案和操作优化。结果表明：使用凝汽器在线能效评估方法可以在保证凝汽器效率的基础上降低高浓缩倍数下的凝汽器结垢风险,帮助电厂实现高节水目标。     

TOPSIS方法应用中若干问题的探讨

应用效用函数理论分析了常用TOPSIS函数,从无差异曲线和边际替换率角度获得无差异曲面为平面族和超球面族两种基本TOPSIS价值函数,基于"差异驱动"原理建立了两类四种评价模型,提出了基于加速遗传算法的优化求解客观权重方法,并将其应用于丰满水库防洪调度决策中,在验证方法有效性的同时比较了不同偏好TOPSIS函数和不同权重确定方法对TOPSIS法的影响。结果表明,该方法更能体现经典的理想点法思想,TOPSIS函数在评价时对评价结果影响明显,但权重对评价结果的影响较大。     

节水增发效益评估方法研究

为更全面准确地评价不同水电站或同一水电站不同年份的优化调度工作,在原有考核指标的基础上,补充提出了节水增发程度指标,讨论了优化模型与径流预报信息对节水增发工作的价值,并以甲、乙两水电站为例分析了指标的有效性及两水电站的随机模型价值(V_(SS))和完全信息价值(E_(VPI))。算例分析表明,节水增发程度指标能有效评估水电站优化提升空间及水电站优化程度;通过评价水电站随机模型价值(V_(SS))和完全信息价值(E_(VPI)),可确定优化模型及径流预报信息对提升水电站发电量的最大贡献裕度,有利于提升水电站增发工作效率。     

基于TOPSIS灰色关联投影法的火电厂节能综合评价与权重灵敏度分析

针对火电厂节能评价的特性,将TOPSIS、灰色关联理论和矢量投影方法引入火电厂状态性能评估,提出了一种基于理想点灰色关联投影的综合评价方法,并采用组合赋权的思想,将Delphi法与序列综合法相结合来确定指标的权重,提高了火电厂节能评价的科学性、客观性.运用该算法对5台600 MW机组进行综合评价,并对主观赋权得到的权值进行灵敏度分析,结果表明:经济性和可靠性指标在机组综合评价中仍然占主导地位,基于TOPSIS灰色关联投影法的评价模型不仅能对机组的节能状态进行定量评价,而且评价鲁棒性强,为电厂决策者制定节能政策、提高节能潜力提供了依据.     

基于最优权重融合的火电机组智能燃烧优化方案评价

目的  随着人工智能技术的发展,基于智能优化算法的燃烧优化方案层出不穷,如GA、PSO、FPA等,这些方案各有优缺点。依托智慧电厂平台开发实时燃烧优化系统时,需要权衡选择最佳技术方案。 方法  针对传统TOPSIS法的权重赋值主观性较强的问题,提出了最优权重融合法对其进行改进,并利用改进TOPSIS法建立了火电机组智能燃烧优化方案评价体系。从优化效果、优化周期、可靠性三个方面对GA、AGA、PSO、FPA、CSO和GSA六种方案进行综合评价。 结果  结果表明：经过MCD指标分析体系和与传统方法对比的双重验证,改进TOPSIS法的赋权与MCD指标重要性排序一致,相比于传统TOPSIS法更能辨别出各方案的优劣,其结果更符合实际生产过程的要求,具有客观性强、准确性好的优点。 结论  文章研究成果可以为火电机组燃烧优化方案的抉择提供有价值的参考。     

基于太阳能加热的沼液负压蒸发浓缩研究

研究不同加热方式(电加热或太阳能加热)、不同参数条件下沼液负压蒸发浓缩的效果,比较了不同因素对沼液浓缩的影响.主要研究结果如下:随着真空度、初始pH值或加热温度的升高,蒸发速率逐渐升高,NH3-N和TN的保留率和浓度逐渐降低,TP和TK的养分浓缩效果增强.综合考虑体积浓缩倍数、养分浓缩效果和养分保留率,最优组合取温度8...     

考虑综合贡献度的虚拟电厂内部效益分摊机制研究

基于虚拟电厂竞价理论和调度模式的研究基础,从虚拟电厂运营商角度,进一步研究考虑综合贡献度的虚拟电厂内部效益分摊机制。首先拟定虚拟电厂运行模式为多投资主体的商业型虚拟电厂,分析虚拟电厂参与电力市场交易盈利场景;其次,从安全性、经济性、风险性这3个方面设计综合贡献度评价指标,并搭建基于TOPSIS的灰色关联度综合评价模型;最后,通过案例分析验证了指标的适用性和方法的可行性。该研究成果弥补了有关多投资主体虚拟电厂运营效益分摊方面的研究不足,对虚拟电厂运营商运行管理多投资主体的商业型虚拟电厂有借鉴意义。     

基于场景生成与IGDT的风光-碳捕集-P2G虚拟电厂经济调度

为了有效降低风光出力与负荷预测的不确定性对虚拟电厂调度运行的影响,提出了基于场景生成与信息间隙决策理论（IGDT）的经济调度优化模型。通过Copula函数与非参数核密度估计方法构建风光出力联合分布模型,并利用蒙特卡洛模拟与k-means聚类得到典型场景。利用区间约束对负荷预测的不确定性进行建模,构建不同风险偏好下的调度优化模型。以典型的虚拟电厂系统进行算例分析,验证了所建立模型可以为不确定性影响下的虚拟电厂经济调度问题提供解决方案。     

采用主成分分析法综合评价电站机组的运行状态

为解决电厂机组运行优化、状态监测与故障诊断中涉及到的机组运行状态的综合评价问题,提出用主成分分析(PCA)方法,建立了电厂机组的综合评价指标的思想.介绍了主成分分析法的原理,并应用该方法对某电厂机组的实际运行状态进行了综合评价.结果表明:该方法消除了主观因素对评价的影响,得到的综合评价指标可对汽轮机进行定量评价,也可为机组状态在线监测提供依据.     

A novel multiobjective charging optimization method of power lithium‐ion batteries based on charging time and temperature rise

Power lithium‐ion batteries have been widely utilized in energy storage system and electric vehicles, because these batteries are characterized by high energy density and power density, long cycle life, and low self‐discharge rate. However, battery charging always takes a long time, and the high current rate inevitably causes great temperature rises, which is the bottleneck for practical applications. This paper presents a multiobjective charging optimization strategy for power lithium‐ion battery multistage charging. The Pareto front is obtained using multiobjective particle swarm optimization (MOPSO) method, and the optimal solution is selected using technique for order of preference by similarity to ideal solution (TOPSIS) method. This strategy aims to achieve fast charging with a relatively low temperature rise. The MOPSO algorithm searches the potential feasible solutions that satisfy two objectives, and the TOPSIS method determines the optimal solution. The one‐order resistor‐capacitor (RC) equivalent circuit model is utilized to describe the model parameter variation with different current rates and state of charges (SOCs) as well as temperature rises during charging. And battery temperature variations are estimated using thermal model. Then a PSO‐based multiobjective optimization method for power lithium‐ion battery multistage charging is proposed to balance charging speed and temperature rise, and the best charging stage currents are obtained using the TOPSIS method. Finally, the optimal results are experimentally verified with a power lithium‐ion battery, and fast charging is achieved within 1534 s with a 4.1°C temperature rise.     

Thermodynamic multi-objective optimization of a solar-dish Brayton system based on maximum power output,thermal efficiency and ecological performance

Solar-dish Brayton system driven by the hybrid of fossil fuel and solar energy is characterized by continuously stable operation, simplified hybridization, low system costs and high thermal efficiency. In order to enable the system to operate with its highest capabilities, a thermodynamic multi-objective optimization was performed in this study based on maximum power output, thermal efficiency and ecological performance. A thermodynamic model was developed to obtain the dimensionless power output, thermal efficiency and ecological performance, in which the imperfect performance of parabolic dish solar collector, the external irreversibility of Brayton heat engine and the conductive thermal bridging loss were considered. The combination of NSGA-II algorithm and decision makings was used to realize multi-objective optimization, where the temperatures of absorber, cooling water and working fluid, the effectiveness of hot-side heat exchanger, cold-side heat exchanger and regenerator were considered as optimization variables. Using the decision makings of Shannon Entropy, LINMAP and TOPSIS, the final optimal solutions were chosen from the Pareto frontier obtained by NSGA-II. By comparing the deviation index of each final optimal solution from the ideal solution, it is shown that the multi-objective optimization can lead to a more desirable design compared to the single-objective optimizations, and the final optimal solution selected by TOPSIS decision making presents superior performance. Moreover, the fitted curve between the optimal power output, thermal efficiency and ecological performance derived from Pareto frontier is obtained for better insight into the optimal design of the system. The sensitivity analysis shows that the optimal system performance is strongly dependent on the temperatures of absorber, cooling water and working fluid, and the effectiveness of regenerator. The results of this work offer benefits for related theoretic research and basis for solar energy industry.     

Evaluation of power plants to prioritise the investment projects using fuzzy PROMETHEE method

Increasing population growth of Iran, and consequently, increasing the annual energy consumption has made the construction of more than 3000?MW power plant necessary. Taking into account various criteria, some power plants have been evaluated and ranked to select the most appropriate power plant for investment. For this purpose, three aspects and seven main criteria for evaluating power plants have been determined. Afterward, weights of sub-criteria have been determined by Analytical Network Process method, and eventually, power plants have been ranked by a multi-criteria decision-making (MCDM) method (i.e. fuzzy PROMETHEE II). Moreover, a comprehensive sensitivity analysis has been carried. Finally, power plants have been ranked by fuzzy technique for order preference by similarity to ideal solution (TOPSIS) method once again. Since the value of Spearman Correlation Test for two implemented methods is equal to 0.98, it can be concluded that fuzzy PROMETHEE II performs as well as fuzzy TOPSIS in ranking alternatives.     

Multi-criteria design optimization and thermodynamic analysis of a novel multi-generation energy system for hydrogen,cooling, heating,power, and freshwater

The main focus of this paper is to present thermodynamic and economic analyses and multi-objective optimization of a novel geothermal-solar multigeneration system. The system aims to produce hydrogen, freshwater, electricity, cooling load, and hot water and designed based on geothermal and solar energy. After modeling and thermodynamic and economic analysis, exergy destruction rate, exergy efficiency and, cost rate were calculated for each component of the system. The results showed that the highest amount of exergy destruction was related to parabolic trough collectors (PTCs) and absorption chillers. To select the geothermal fluid of the organic Rankine cycle (ORC), several different fluids were investigated, among which isobutene was selected. By using the Group method of data handling (GMDH) neural network, a mathematical relationship was obtained between the inputs and outputs of the problem and were given as inputs to the non-dominated sorting genetic algorithm II (NSGAII)alg. The final optimal point was obtained applying the technique for order of preference by similarity to ideal solution (TOPSIS) decision criterion at which the exergy efficiency and cost rate were calculated to be 21.63% and 63.89 $/h, respectively. The meteorological data of the Zanjan, Isfahan, and Bandar Abbas cities were used to calculate the performance accurately at the TOPSIS selection point. To provide a comparison between different cities, the performance of the system was evaluated on September 17 as a sample day. On this day, the proposed system produces 26.38 kg of hydrogen and 373.8 m³ of freshwater in Isfahan.     

基于模型预测的多模式供热电厂机组间负荷优化分配调度研究

为解决热电厂机组间负荷分配不合理的问题,提出一种基于模型预测的多模式供热电厂多机组间负荷实时优化分配方法。基于模块化建模原理构建热电厂全厂范围的机理仿真模型,并运用运行数据对模型辨识校准,根据机组特性和电网调峰补贴政策,建立全厂的运行经济性收益评估模型,进而设计基于粒子群算法的负荷实时优化方法,借助性能预测模型预测评估各方案的经济性。以某包含高背压、切缸、抽汽、光轴4种供热模式机组的电厂为例,对不同电、热负荷组合工况下的厂内负荷进行优化分配研究。应用结果表明：该方法可根据热、电负荷的实时指令在线获得经济性优化的厂内机组间负荷分配方案。     

An Efficient Summer Operation Scheme for a Thermal Power Plant Air Cooling System based on Electric Peak Shaving

We proposed a novel efficient operation scheme for a thermal power plant’s air-cooling system based on peak shaving, in order to cope with high ambient temperature in summer. We introduced an absorptiongeneration equipment with water/lithium working pairs into the air cooled condenser(ACC) to reconstruct the traditional thermal power plant, and established a dynamic thermodynamic model adopting Ebsilon code. We studied the thermodynamic performance variation of the reconstructed thermal power pl...     

火电厂单元制循环水系统离散优化模型及其应用

对水量不连续变化的单元制循环水系统提出了一种离散优化模型,该模型以等效益点迭代计算来决定泵组切换时的临界工况。以黄台电厂7号机组为例,利用本模型对循环水系统进行了优化运行研究,确定了机组在不同季节、不同负荷最经济的循环水泵运行编组方式。效益分析表明,对于300MW机组,循环水系统离散优化可使电厂标准煤耗降低0．5～0．7g/(kWh)。文中根据热力试验数据,总结出凝汽器传热系数的一个经验公式,可供同类机组参考。     

Energy efficiency drivers in South Africa: 1965–2014

This paper presents an assessment of energy performance in South Africa from 1965 to 2014 using the technique for order of preference by similarity to ideal solution (TOPSIS). In this research, TOPSIS is used first in a two-stage approach to assess how energy in South Africa has performed using the most frequent indicators adopted by the literature. Afterwards, in the second stage, neural networks are combined with TOPSIS results as part of an attempt to produce a model for energy performance with good predictive ability. The results reveal different impacts of contextual variables such as the rise of China in foreign trade, the Apartheid Regime, and oil shocks on energy performance in South Africa.     

Optimization of an atmospheric air volumetric central receiver system: Impact of solar multiple,storage capacity and control strategy

Portugal has a high potential for concentrated solar power and namely for atmospheric air volumetric central receiver systems (CRS). The solar multiple and storage capacity have a significant impact on the power plant levelized electricity cost (LEC) and their optimization and adequate control strategy can save significant capital for the investors. The optimized proposed volumetric central receiver system showed good performance and economical indicators.For Faro conditions, the best 4 MW_e power plant configuration was obtained for a 1.25 solar multiple and a 2 h storage. Applying control strategy #1 (CS#1) the power plant LEC is 0.234 €/kWh with a capital investment (CAPEX) of € 22.3 million. The capital invested has an internal rate of return (IRR) of 9.8%, with a payback time of 14 years and a net present value (NPV) of € 7.9 million (considering an average annual inflation of 4%). In the case of better economical indicators, the power plant investment can have positive contours, with an NPV close to € 13 million (annual average inflation of 2%) and the payback shortened to 13 years.